In-bound telemarketing system for processing customer offers

ABSTRACT

A computer-implemented system and method for processing applications for products or services based on solicited offers made to consumers are provided. A plurality of offers are communicated to a plurality of consumer recipients using a computer, each offer being identified by a solicitation identifier and an offer identifier. Offer information of said offers is stored in an offer database that further includes consumer identification information associated with the consumer recipients. A response to a specific offer is received from a specific consumer recipient at a VRU via a communication link with the specific consumer recipient. At least some offer identification data and consumer identification data is received from the specific consumer recipient at the VRU. Data received at the VRU is used to query the offer database to identify other targeted offers targeted to the specific consumer recipient and data associated with those other targeted offers, including consumer identity verification data. The identity of the specific consumer recipient is verified based on the consumer identification data and the consumer identity verification data. The communication link is transferred from the VRU to a live agent. The live agent is provided with (a) information received from the specific consumer at the VRU and (b) data from the query of the offer database including data regarding other targeted offers.

RELATED APPLICATION

This application is generally related by subject matter to U.S.application Ser. No. 10/634,091 on Sep. 4, 2003 and entitled “System AndMethod For Financial Instrument Pre-Qualification And Offering.”

FIELD OF THE INVENTION

The present invention relates to a system and method for handlingin-bound telemarketing calls when a consumer responds to a targetedoffer (“solicited”) or a generalized marketing overture (“unsolicited”).

BACKGROUND OF THE INVENTION

Financial institutions and other merchants use telemarketing to marketand distribute products and services. Telemarketing can involve thetelemarketer calling customers directly to market a product (“out-boundtelemarketing”), and it can also involve receiving calls from customersin response to an offer or overture previously received by the customer(“in-bound telemarketing” or “IBTM”), or for other reasons the customerinitiates a call to the seller. The present invention is generallydirected to handling in-bound telemarketing calls when a consumerresponds to a targeted offer directed specifically at the consumer(“solicited offer”) or a generalized marketing overture to a pluralityof individuals (“unsolicited offer”). While other merchants, products,and offerees are contemplated herein, a typical scenario involves a banktelemarketing a financial product such as a credit card or creditcard-related product or service to an existing bank customer or aplurality of existing bank customers, or to a potential bank customer orplurality of potential bank customers.

It is known that solicited offers are offers which can be sent by mail,the Internet, or by out-bound telemarketing whereby a bank customer isoffered a product such as a credit card. The solicited offer willusually include identifying information such as a solicitation number,an offer number, and a toll free number for the consumer to respond.Multiple offers may be extended over time to the same consumerrecipient, and typically the bank maintains a database that storessolicitation numbers, offer numbers, and underlying data related to thatoffer, such as the consumer's name, address, etc. The database may storeinformation that was used in extending that offer, such as any creditdata, income data, and household data. Thus, looking up a solicitationnumber for consumer A responding to offer 1 may provide underlyinginformation related to that offer 1. The solicitation number typicallyidentifies the offer and solicited customer.

For solicited offers, when a caller responds by calling the bank's tollfree number, the call is typically routed to a Voice Response Unit(VRU). The VRU may solicit the caller to input data, including thesolicitation number and/or offer number. The VRU then accesses theinternal offer database to acquire the information associated with thesolicitation number, particularly the data associated with the specificoffer at issue. Then the VRU issues a query to a third party creditbureau. The credit bureau applies credit decisioning rules previouslysupplied by the bank. The credit bureau returns an “approved” or“declined” response to the VRU. Typically, the VRU does not give thecaller an immediate yes/no answer; rather, the call is then routed to alive agent. Equipped with the limited information from the VRU, the liveagent denies the customer's request or approves the request and enrollsthe customer in the offered financial program, product, or service. Inthe prior art, the live agent typically receives limited customer andtransaction information from the VRU. As a result, prior art approachesto handling solicited offer responses require a significant amount oftime for the live agent to collect data from the caller.

Unsolicited offers are not directed to individual consumers. While theytypically include a toll free number, they do not have solicitationnumbers or offer numbers. Thus, the process after initial information iscollected from the caller follows the process described above, exceptthat there is no database lookup. Instead, the approval information isdetermined based entirely on information received from the customerduring the call.

Deficiencies exist in the conventional approaches for call processingfor solicited and unsolicited offers. In both types of telemarketing,the systems and methods for identifying and verifying informationprovided by the customer are limited. Existing systems generally accepta customer's address without checking it against other data. Inaddition, voice recognition technology used by VRUs are limited in theirability to identify customer information provided in the customer'sspeech during the call, such as the customer's address. Further, limitedinformation is provided to the live agent, and therefore the live agenthas a limited ability to market additional products and services thatmay be relevant to the customer. For the solicited offers, the limitedinformation provided to the agent also prevents the agent from followingup on prior offers that may have been extended to the customer. Further,the limited information provided to the live agent undermines efficiencybecause the agent must collect significant information from the callerafter the call is routed to the live agent.

These and other drawbacks exist with current systems and methods.

SUMMARY OF THE INVENTION

Accordingly, various embodiments of the present invention may bedirected to a system and a method for processing applications forproducts or services based on solicited offers made to consumers. Acomputer-implemented system and method for processing applications forproducts or services based on solicited offers made to consumers areprovided. A plurality of offers are communicated to a plurality ofconsumer recipients using a computer, each offer being identified by asolicitation identifier and an offer identifier. Offer information ofsaid offers is stored in an offer database that further includesconsumer identification information associated with the consumerrecipients. A response to a specific offer is received from a specificconsumer recipient at a VRU via a communication link with the specificconsumer recipient. At least some offer identification data and consumeridentification data is received from the specific consumer recipient atthe VRU. Data received at the VRU is used to query the offer database toidentify other targeted offers targeted to the specific consumerrecipient and data associated with those other targeted offers,including consumer identity verification data. The identity of thespecific consumer recipient is verified based on the consumeridentification data and the consumer identity verification data. Arequest is issued to a credit bureau for an approval result returned tothe VRU. The communication link is transferred from the VRU to a liveagent. The live agent is provided with (a) information received from thespecific consumer at the VRU, (b) data from the query of the offerdatabase including data regarding other targeted offers, and (c) theresults of the credit bureau request.

According to another embodiment of the invention, a system forprocessing a specific consumer recipient offer is provided. An outputdevice communicates, using a computer, a plurality of offers to aplurality of consumer recipients, each offer being identified by asolicitation identifier and an offer identifier. A database stores offerinformation of said offers in an offer database that further includesconsumer identification information associated with the consumerrecipients. An input device receives a response to a specific offer froma specific consumer recipient at the VRU via a communication link withthe specific consumer recipient. The input device also receives at leastsome offer identification data and consumer identification data from thespecific consumer recipient at the VRU. A processor uses data receivedat the VRU to query the offer database to identify other offers targetedto the specific consumer recipient and data associated with those othertargeted offers, including consumer identity verification data. Theprocessor also verifies the identity of the specific consumer recipientbased on the consumer identification data and the consumer identityverification data. A transfer mechanism transfers the communication linkfrom the VRU to a live agent, wherein the live agent is provided with(a) information received from the specific consumer at the VRU and (b)data from the query of the offer database including data regarding othertargeted offers.

According to another embodiment of the invention, a computer-implementedmethod for processing applications for products or services based onsolicited offers made to consumers is provided. A plurality of offersare communicated to a plurality of consumer recipients using a computer.Offer information of said offers is stored in an offer database. Aresponse to a specific offer from a specific consumer recipient isreceived at a communication processor via a communication link with thespecific consumer recipient. At least some offer identification data andconsumer identification data is received from the specific consumerrecipient at the communication processor. Data received at thecommunication processor is used to query an offer database to identifyother offers that may be targeted to the specific consumer recipient anddata associated with those other targeted offers. The communication linkis transferred from the communication processor to a live agent. Thelive agent is provided with (a) information received from the specificconsumer at the communication processor and (b) data from the query ofthe offer database including data regarding other targeted offers.

According to another embodiment of the invention, a computer-readablemedium encoded with computer program code to process an offer isprovided. The program code effective to store specific consumerrecipient data associated with a specific consumer recipient. Theprogram code is effective to distribute an offer to the specificconsumer recipient after the act of storing, wherein the offer comprisesan offer identifier associated with the offer and the specific consumerrecipient. The program code is effective to receive a response to theoffer from the specific consumer recipient, wherein the responsecomprises the offer identifier. The program code is effective toidentify the stored specific consumer recipient data based on the offeridentifier. The program code is effective to pass the stored specificconsumer recipient data to a live agent. The program code is alsoeffective to determine an offer result.

According to another embodiment of the invention, a method forprocessing a customer offer is provided. An offer is distributed to acustomer. A response to the offer is received from the customer througha customer communication device, wherein the response comprises customeraddress information. The location of the customer communication deviceis automatically identified. The customer address information isverified based on the location of the customer communication device.

Other embodiments are also within the scope of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a system for processing an offer according to anembodiment of the invention.

FIG. 2 depicts a flow-chart for processing a solicited offer accordingto an embodiment of the invention.

FIG. 3 depicts a flow-chart for processing an unsolicited offeraccording to an embodiment of the invention.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

The embodiments described herein solve many problems with existingsystems and methods. In some embodiments, customer information such ashome address can be identified and verified using voice recognitiontechnology, automatic number identification, GPS technology, and othertechnologies.

In some embodiments, previously stored customer information, newlyreceived customer information, and credit bureau results are allavailable to the live agent during the call. Based on all of thisinformation, additional offers (e.g., cross-selling) may be made to thecustomer that are relevant to the customer. In these embodiments, thelive agent may have more information to inform a decision to approve acustomer for a given product or service, such as a credit card product.This leads to more accurate approvals and therefore higher profits,since inaccurate approvals can cause losses to the bank when anunqualified customer defaults on a payment, for instance. In theseembodiments, the live agent also has more information for selectingadditional offers appropriate to the customer.

According to another embodiment of the invention, the internal offerdatabase lookup retrieves all offers (i.e., for all offer numbers)extended to that caller rather than the single offer that prompted thecustomer's response. This gives the live agent a full history of theoffers extended to that consumer so that the live agent can make fullyinformed decisions on the present offer and for renewing or otherwiserevisiting other offers, such as offers previously extended to thatcustomer.

OVERVIEW AND SYSTEM ILLUSTRATION

According to one exemplary embodiment as depicted in FIG. 1, the systemcomprises a processor 2 that communicates with one or more customers 8a-8 n, a credit bureau 12, and one or more live agents 10 a-10 n. Theprocessor 2 may also be coupled to a database 6.

The customers 8 may comprise potential customers of financial products,such as offerees who have received a financial product solicitation. Forinstance, a customer 8 a may be an individual person (or other entitysuch as a corporation) who has received an offer to obtain a productsuch as a credit card. Another customer 8 b may be an individual personwho has received an offer to obtain a specific stored value cardproduct. Another customer 8 c may be an individual who received an offerto refinance a home and another offer to obtain a credit card sponsoredby a particular retailer. Other customers 8 d-8 f may not receive anyspecific offer.

Live agents 10 a-10 n may be live persons associated with the processor2 who communicate with the processor 2. The live agents 10 may alsocommunicate with customers 8, either directly, or indirectly through theprocessor 2. Accordingly, it should be appreciated that the processormay receive information from the customer 8 (and/or communicateinformation to the customer 8) directly, or indirectly through a liveagent 10. Offer information may be communicated between and among thelive agents 10, customers 8, processor 2, and database 6. Thecommunication between and among these elements may be via any suitablecommunication system or network. For instance, the communication may bevia telephone, email, Internet, wireless network, or other means ofcommunication. Accordingly, the customer may use a telephone, PDA, textmessaging device, computer, processor, or other communication device tocommunicate with the processor 2 and/or live agents 10.

The credit bureau 12 may process customer 8 information and determineone or more credit scores for one or more customers 8. In determining acredit score or other information, the credit bureau 12 may access andprocess credit history and other credit information associated with aspecific customer 8 a. The credit bureau 12 may pass the credit scoresto the processor 2 and/or one or more live agents 12. According to oneembodiment, processor 2 may be operated by a financial servicesprovider, such as a bank, and credit bureau 12 may be a third partyperforming credit processing based on bank-supplied decisioning rules.

The processor 2 may comprise a processor, server, hub, intranet, voiceresponse unit (VRU), computer, network, and/or other processing element.For instance, the processor 2 may comprise a credit card offerprocessing system. The processor 2 may also comprise a computer systemthat handles the enrollment and maintenance of financial accounts suchas credit card accounts and bank accounts. For instance, the processormay comprise a bank computer system. The processor 2 may comprise inputand output devices for communicating with database 6, customers 8, liveagents 10, and credit bureau 12.

According to the exemplary embodiment, processor 2 includes offerdistribution module 22, VRU module 24, offer identifier module 26,customer information module 28, verification module 30, ANI module 32,location module 34, credit bureau module 36, additional offer module 38,approval module 40, and other module(s) 42. Further, details of theseexemplary modules in processor 2 are described below.

The database 6, sometimes referred to herein as the “internal offerdatabase,” may store information, such as information received from theprocessor 2, live agent 10, customer 8, and credit bureau 12. Thedatabase 6 may be part of the processor 2 or it may be coupled to theprocessor 2. The database 6 may comprise a plurality of databases 60-68.According to one embodiment, database 6 includes the following databasemodules: offer database 60, customer database 62, additional offerdatabase 64, location database 66, and other database 68.

Offer database 60 may store offer information, such as offer terms andfeatures, offer identifiers corresponding to one or more offers,solicitation numbers, and customer data. Offer database 60 may includecredit score data that was used in extending an offer. An offer maycomprise an offer for the consumer to apply for (or purchase) afinancial product (e.g., a certificate of deposit, a stored value cardsuch as a gift card, a credit card, etc.), establish an account (such asa credit card account, checking account, savings account, etc.), orotherwise establish a relationship with a financial entity (obtain aloan or other financing arrangement, enroll in a program such as arewards program or travel benefit program, obtain account protection,expand a current account or program, etc.), banking online, smallbusiness accounts, mutual funds, stock broker relationships, or it maycomprise any other kind of merchant and/or bank offer. Other offers maybe contemplated herein. One or more offers (each identified by an offeridentifier) may be distributed to a customer 8 a in a solicitation(identified by a solicitation number). It should be understood that, asused herein, the term “offer” is to be broadly construed to mean atargeted or untargeted solicitation for the consumer to apply for (orpurchase) a product or service. Though referred to herein as offers, notall such overtures are offers in the contractual sense since they arenot necessarily legally binding upon mere consumer acceptance.

The database 60 may associate each solicitation number with one or morespecific offers and one or more specific customers 8. Thus, a singlesolicitation identifier may associate a single offer with a singlecustomer 8 who received the offer. Alternately, a single solicitationmay associate a plurality of offers with a single customer 8 a whoreceived the offers. The database may also store information describingthe offer and customer, such as the type of financial product and thename and/or address the customer. As used herein, an “offer identifier”refers to any identifier relating to an offer, such as a solicitationidentifier or an “offer identifier” as described above.

Offer database 60 may store information describing each offer, such asthe expiration time of the offer, the customer 8 qualificationsnecessary for obtaining the offered product or service, and other offerfeatures. The offer database 60 may also store information about theoffered product or service, including the term of the product orservice, the cost of the product or service, business rules governingthe product or service, and other features associated with the productor service.

Database 60 may also store other offer information and customerinformation, such as customer information associated with the offerinformation. For instance, an offer identifier may comprise anidentifier (e.g., “ABC123”) that is uniquely matched with a specificoffer, such as an offer to obtain a platinum Visa credit card sponsoredby SponsorCo and issued by BankCo.

Offer database 60 may also store information associating one or morespecific offers (and offer identifiers) with one or more specificcustomers 8 a-8 n. For instance, offer identifiers ABC123 and XYZ789 maybe associated with specific customer 8 a. In another embodiment, offeridentifiers ABC123 and XYZ789 may both be associated with more than onecustomer, such as customers 8 a-8 g. The identifier-customer 8associations may correspond to offers that are distributed to a specificcustomer 8 a or groups of customers 8.

Customer database 62 may store customer 8 information. Customer 8information may comprise any of the following types of information:name, address, birth date, social security number, credit score, income,job status, time at current residence, past residence information,password, PIN, accounts, associated offers, associated financial orother products, and other personal or financial information. Forinstance, a customer 8 a may utilize several different financialproducts and services offered by a specific bank. The customer database62 may store information related to those accounts and services, such asthe amount of activity on a specific account or the last time a customerused a particular service.

Customer database 62 may also store customer voice information, such asinformation regarding the speech patterns of a customer. Thisinformation may enable the processor 2 to subsequently identify thecustomer by the speech patterns.

Customer database 62 may also store customer preference information.This information may include information regarding social and/oreconomic data related to the customer, such as the customer's purchasinghistory and residence preferences, customer selections on a merchant webpage, words spoken (or other inputs) by the customer in prior phonecalls or communications with the merchant, prior requests made by thecustomer, and other customer-related data. For instance, the database 62may store a list of purchases made by the customer using a particularbank credit card.

Additional offer database 64 may store information about one or moreoffers that may be provided to one or more customers 8. The database 64may store information relating to any of the following: one or moreoffers associated with a particular customer, such as an offer for whichthe particular customer 8 a is pre-qualified (or is not pre-qualified),or for which the customer has a high likelihood of approval; terms andconditions of offers (such as offers associated with pre-approvedcustomers); and one or more offers which may be of special interest to aspecific customer 8 a based on customer preference data, customerbehavior data, or other customer data. The database 64 may also store alist of offers previously made to a customer.

The additional offer database 64 may also store business rules thatdetermine which offers and/or types of offers may be provided to one ormore customers 8 or types of customers. For instance, database 64 maystore information indicating that offer X should only be provided tocustomers 8 who have an existing credit card account with a particularbank. It may also determine that a financial account product thatincludes a free DVD player should be provided to customers who havepurchased over $1000 of home theater equipment in a one-month periodwithin the past year.

Generally, additional offer database 64 may be used to generate newsolicited offers to be distributed in the usual fashion, or to generate“cross-sell” offers made when a caller calls in response to a differentoffer.

Location database 66 may store location information. The locationinformation may comprise a list of streets or other address informationwithin a particular area code or zip code. The location module 34 mayaccess the location database to identify the names of streets that arelocated in a specific zip code provided by a customer 8. The locationmodule 34 may also identify the names of streets in or near theidentified zip code or area code. The location database may also storeother customer, offer, and financial-related location information.

Other database(s) 68 may store other information relating to thecustomers 8, live agents 10, credit bureau 12, and processor 2.

It should be understood that each of the plurality of databases 60-68may store information linked to information in other databases 60-68.For instance, the offer database 60 may store information that links aspecific offer with customer information in the customer database 62.

The processor 2 may comprise a plurality of modules 22-42. Each modulemay comprise a computer or other processor, including one or more inputand output devices. The processor 2 may accordingly be a systemcomprising a plurality of computer systems linked together on a network.Thus, a person of ordinary skill in the art will recognize that thevarious modules can be implemented on a single computer device, oracross multiple computer devices.

The modules which communicate with a customer may be equipped with voicerecognition devices to distill words from the speech of the customer.These modules may also employ various other well-known methods to obtaininformation from the customer. For instance, these modules may use a VRU(voice response unit) to prompt for information and receive informationfrom the customer.

Offer distribution module 22 may process offer data and customer dataand cause offers to be distributed to one or more customers 8. Offerdistribution module 22 may apply offer business rules stored in theoffer database 60 to create a population of customer 8 offerees who willreceive the offer in a solicitation. Offer distribution module 22 mayrely on credit score data from credit bureau 12 in creating these orother offers.

The offer distribution module 22 may also comprise an output apparatusfor passing offers to customer 8. For instance, module 22 may comprise aprinter to print written offers (e.g., mail solicitations), anelectronic output device to send emails, text messages, or otherelectronic messages to customer 8, automatic dialing device toautomatically dial customer phones, and/or an output device for passinga request to a live agent 10 to provide one or more offers to one ormore customers 8.

The VRU module 24 may comprise an automated telephone system such as avoice response unit (VRU). The VRU may perform any of the followingfunctions: receive customer 8 phone calls; prompt customers 8 forcustomer information and offer information; receive customer 8 and offerinformation; and pass information to the processor 2 and/or to one ormore live agents 10. Preferably, the module 24 receives the informationover the phone. However, with appropriate interfaces and/or interfaceadapters well known to an artisan of ordinary skill, the module 24 mayreceive the information over the phone, email, text messaging, theInternet (e.g., via VOW), a direct data connection, or other means. Theinformation may be received in encrypted form, and the VRU module 24 mayhave a de-encryption device to decode the information.

The VRU module 24 may comprise a typical bank VRU system for receivingresponses to offers such as credit card offers. The VRU module 24 mayalso comprise a server for accomplishing the above functions over theInternet. For instance, the VRU module 24 may comprise a website of abank (e.g., a website that does not use an actual VRU).

Offer identifier module 26 may identify offers and offer identifiers,e.g., offer identifiers received from customers 8. For instance, acustomer 8 may provide an offer identifier to the processor 2 (i.e., tothe VRU module 24) or to a live agent 10, and the offer identifiermodule 26 may identify the offer identifier and then access the offerdatabase 60 to identify any offers associated with the offer identifier.The offer identifier module 26 may also determine whether a particularcustomer 8 a (e.g., the customer 8 a who provides the offer identifier)is associated with the offer (and/or the offer identifier). In this way,the offer identifier module 26 may determine whether a specific customer8 a was an intended (or valid) recipient of a specific offer.

Customer information module 28 may identify a customer 8 and receive,identify, access, and store customer 8 information. For instance, whenthe processor 2 receives information from a customer 8 a, the customerinformation module 28 may process the information and store it in thecustomer database 62. Customer information may comprise any of thefollowing information related to the customer: name, address, time atcurrent address, email address, social security number, mother's maidenname, income (e.g., personal or household), asset information (e.g.,existence of or amount in checking or savings account, or value ofinvestments or holdings), housing payment information (e.g., monthlyrental or mortgage payment), employment history, current employmentstatus, time at current employment, credit score (or other credit data),address history, work address, home and/or work phone number, benefitinformation, date of birth, number of dependents, and/or other customerinformation. Customer information may also comprise customer preferenceand behavior information, such as credit card purchase activity.Customer information may also comprise all of the products and services(e.g., provided by the merchant/bank) that are presently or have beenused by the customer, and it may also include a list of prior andcurrent offers made by the merchant to the customer.

The bank or processor 2 may obtain this information in the regularcourse of business as the bank obtains information from its customers 8.The information may also be obtained (and verified) during atelemarketing call, as described in FIGS. 2 and 3.

The module 28 may comprise voice recognition processors and softwareused to identify words spoken by the customer 8 a, e.g., words spokenover the phone to the VRU module 24. Thus, if the customer 8 a speaks anaddress in response to a prompt to provide the address, the module 28may determine the words spoken by the customer and identify the address,e.g., “123 N. Main Street, Centerville, Ind., zip code 47330.”

The voice recognition technology may use different algorithms to distillwords from caller speech depending on the location of the caller. Forinstance, the voice recognition technology may use one algorithm tointerpret speech from callers in one city or region, and anotheralgorithm may be used for callers in another city or country, where adifferent dialect or language is used. For instance, callers in theSouthern United States may have different speech patterns for words (andthey may use different types of words) compared with callers in New YorkCity.

Verification module 30 may verify customer information, such as customerinformation stored in the customer database 62. For instance, personalinformation of an existing bank customer 8 a may be stored in thecustomer database 62. The customer 8 a may respond to an offer bycalling the VRU module 24 at the processor 2. The VRU module 24 mayprompt the customer 8 a for personal information such as mother's maidenname and social security number, and the customer 8 a may provide suchinformation to the VRU. The verification module 30 may then access thecustomer database 62 to verify that the provided name and socialsecurity number match those on record for that customer 8 a in thecustomer database 62. In this way, the verification module 30 may verifythat the customer 8 a is indeed providing the information, since it isunlikely that another person would know the customer's information.Verification module 30 may also verify information received by othermeans, such as information received or otherwise processed by the othermodules 22-42. The verification module 30 may accordingly satisfy asecurity purpose.

Verification module 30 may also verify the identity of a customer usingvoice recognition processors and comparing received voice information tovoice information stored in the customer database 62. Verificationmodule 30 may also verify a customer's phone number, e.g., by comparinga phone number for the customer stored in the customer database 62 witha number identified by the ANI module 32.

ANI module 32 may verify customer information. For instance, the ANImodule 32 may use automatic number identification (“ANI”) methods anddevices to identify the phone number from which a specific customer 8 acalls the processor 2. For instance, the ANI module 32 may use a “callerID” device as well-known in the art. The ANI module may also identifyother customer-related information, e.g., if the customer 8 a contactsthe processor 2 over the Internet. For instance, the processor 2 mayidentify the IP address of the customer 8 a, or cookie from a previouscontact.

Based on the phone number and/or IP address, the ANI module may identifyother information, such as personal information associated with the IPaddress (e.g., the name and/or address a person who has an account withthe Internet or telephone service provider through which the customer 8a accesses the processor 2). Although the customer 8 a may not be theperson who has the account, the customer 8 a may be related to thatperson, have the same address, or otherwise have personal informationthat is related to the personal information identified by the ANI module32.

Location module 34 may identify the location of a customer 8 a who isaccessing the processor 2. Location module 34 may use GPS and/or“iidigits” technology to identify the general location of caller (or thecaller's phone, e.g., if the phone is equipped with a GPS device). Thelocation module 34 may also receive customer location information (suchas a zip code) after prompting the customer for such information. Fromthe zip code or other address or location information, the locationmodule 34 may identify one or more (or all of) the streets in this zipcode or location, e.g., by accessing the location database 66. Thecustomer could then be prompted to provide a street address, which couldbe matched with the zip code-derived subset of street results.

Credit bureau module 36 may pass information to (and receive informationfrom) a credit bureau 12, such as customer and offer information. Forinstance, the credit bureau module 36 may pass personal customerinformation to the credit bureau 12 and receive a credit score from thecredit bureau 12. The module 36 may provide the credit bureau 12 withbusiness rules, such as rules that define or interpret a customer creditscore. The module 36 may also implement such rules. For instance, themodule 36 may determine that customers having an income below a certainthreshold lose five points on their credit score, and it may pass thisrule to the credit bureau 12. The module 36 may also determine creditscore thresholds and other criteria for various financial products. Forinstance, the module 36 may determine that customers 8 are eligible fora titanium-level credit card if they have a credit score above 700.

Additional offer module 38 may select additional offers to provide toone or more customers 8. The selected offers may be provided tocustomers 8 by a live agent 10 a or by the module 38.

Approval module 40 may approve (and/or pre-approve) one or morecustomers 8 for one or more offers, products, and/or services. Forinstance, the approval module 40 may process customer information, suchas a customer's income, credit history, and/or credit score (e.g., ascore received from the credit bureau 12) to determine whether aparticular customer 8 a is approved for a platinum credit card. Theapproval module 40 may also determine a credit limit, reward program,and any other feature associated with the product. The approval module40 may determine these and other features based on customer informationand/or approval information. The approval information may be stored inthe customer database 62. For instance, the approval module maypre-approve customers 8 for a particular financial product based oncustomer income information and store this information in the customerdatabase 62.

Other module(s) 42 may perform other functions.

It should be understood that the server, processors, and modulesdescribed herein may perform their described functions automatically orvia an automated system. As used herein, the term “automatically” refersto an action being performed by any machine-executable process, e.g., aprocess that does not require human intervention or input.

Illustrative Process

FIG. 2 depicts a flow-chart for processing a solicited offer accordingto an embodiment of the invention.

In block 200 of FIG. 2, customer data and/or offer data is stored. Forinstance, personal information associated with bank customers 8 (orother consumers) may be stored. The customer information may comprisethe name, address, social security number, income, employment history,credit score (or other credit data), address history, or other customerinformation. The bank may obtain this information in the regular courseof business as it obtains information from its customers 8, forinstance. The bank may obtain this information from other sources, suchas public records, credit bureaus, and other databases accessible to themerchant.

The offer data may comprise information relating to one or more offersthat may be distributed to one or more customers in block 210. The offerdata may comprise information about the offered product and/or servicesuch as the terms and provisions of the offer, and it may also compriseoffer identifiers. The offer identifiers may be associated with one ormore customers, and the association information may also be stored.

In block 205, one or more offers are associated with one or morecustomers 8. In some embodiments, an offer is associated with a customer8 a who will receive the offer. This associating action may be prior todistributing the offers to the customers.

For instance, the offer distribution module 22 may email (and/or print)a plurality of solicitations and cause them to be delivered to the emailaddress (or physical address) of one or more customers, or deliveredthrough an automated outbound telephone call.

In block 210, one or more offers are distributed to the one or morecustomers 8. For instance, an offer may be emailed to a bank customer ormailed to the physical address of a person who has transacted with abank partner. The offer may include key terms of the offer, an offernumber, and a solicitation number. The offer may also includeinstructions for contacting the merchant bank (or processor or callcenter associated with the bank). For instance, the offer may include awebsite, an 800 number, an address, and/or other information needed forcontacting the bank.

In block 215, a customer may contact the processor, such as via awebsite or VRU (e.g., VRU module 24). For instance, the customer maycall an 800 number provided with the offer. The 800 number may directthe caller to a call center comprising one or more processors, liveagents, and VRUs. The customer may be immediately transferred to a liveagent, or the customer's call may be answered by a live agent.Preferably, the customer's call is directed to a VRU (e.g., VRU module24).

While a VRU is described for this exemplary embodiment, it should beunderstood that a live agent or other processing element may communicatewith the customer in addition to the VRU. For example, it should beunderstood that an 800 number (provided with the offer) may direct theofferee/customer/caller to a call center comprising one or moreprocessors, live agents, and VRUs. Further, the customer may contact theprocessor over the internet or other networked means rather than via aVRU. The caller may be transferred between and among the variouscomponents of the call center throughout the call. However, thepreferred approach is that the customer is routed immediately, oreventually, to a VRU or other automated device so that certaininformation can be collected from the customer before routing to a liveagent for disposition of the application.

In block 220, customer-provided data such as offer data may be received,e.g., by a live agent, VRU or other processing element. For instance,the processor may prompt the caller for information, and the customermay provide the requested information. The requested information maycomprise one or more offer identifiers, one or more solicitationidentifiers, other offer information, caller name, caller address, andother caller information as described above.

The VRU may receive the information over the phone, or, with appropriateinterface circuitry, a VRU, email, text messaging, the Internet (e.g.,via VOW), a direct data connection, or other means. The information maybe received in encrypted form, and the VRU may have a decryption deviceto decode the information.

The customer may provide such information through any variety of means.The customer may speak the information (e.g., in response to promptsfrom the VRU or live agent), enter text responses via a keypad orkeyboard, or otherwise convey the information to the processor (eitherdirectly or indirectly through the live agent). For instance, thecustomer may use touchtone inputs on a phone.

In block 225, the customer-provided information may be verified (e.g.,by the processor or a live agent). The information may be verified as itis received (on an ongoing basis), or it may be verified at anothertime, such as after all personal information has been received from thecustomer. To verify the information, the processor may compare thereceived information with stored information about the customer (and/oroffer). For instance, the processor may prompt the customer to speak thename of the customer's mother's maiden name and may accordingly receivespeech information corresponding to the mother's maiden name. Theprocessor may identify the mother's maiden name from the received speechinformation. The processor may then access the customer database todetermine whether the identified name matches the mother's maiden namestored for that customer in the customer database 62.

The processor may also verify the identity of the customer by checkingthis information. Further, if voice information has previously beenstored for the customer, the processor may compare the voice information(e.g., speech patterns and timbre) with current voice informationreceived and processed during the call. It should be appreciated thatthis may only be accomplished when the customer's voice is received,e.g., on a phone call. In some embodiments, the processor may prompt thecustomer for a PIN, password, or other code in order to verify theidentity of the caller/customer.

In block 230, stored customer and offer information may be identified,e.g., by the processor. For instance, the VRU module 24 and/orverification module 30 may use voice recognition software to identifythe solicitation identifier, offer identifier, and personal informationof the customer based on the customer's responses to requests for thatinformation. The stored customer data may be data stored in block 200and/or received at block 220, and the offer information may beinformation received at block 220.

In block 235, the VRU may pass a query to a credit bureau, e.g., a queryfor a credit score. The query may comprise customer and offerinformation. For instance, the query may comprise information receivedfrom the customer such as income, employment history, and residencehistory. If needed, customer approval to obtain a credit report may berequested prior to querying the credit bureau.

In block 240, the credit bureau may determine approval information, suchas a credit score of the customer. In determining the approvalinformation, the credit bureau may access and process credit history orother creditworthiness information of the customer. The credit bureaumay also apply business rules provided by the bank to process thecustomer's personal information (such as income and employment history)and credit history information in order to determine a credit score orother approval information.

In block 245, the credit bureau may pass credit and/or approvalinformation such as the consumer's credit score to the processor (orlive agent or other entity). As used herein, “customer approvalinformation” may comprise approval information, denial information, or aresponse that requests additional data or processing. The creditinformation may comprise information used in determining whether toapprove the customer for the offered product or service. The approvalinformation may comprise a determination of creditworthiness, eithergenerally or in specific relation to the offered product.

In block 250, credit information (e.g., credit score), offer information(e.g., the current offer or additional offers for which the customer isapproved), and customer-provided information (e.g., name and income) maybe passed to the processor and/or a live agent. For instance, theprocessor (e.g., the VRU) may transfer the call to a live agent afterreceiving information from the customer, credit bureau, and modules anddatabases. The credit, offer, and customer-provided information may beall or a portion of the information received from (or processed by) thecredit bureau, processor and databases, and customer in any of theabove-described blocks. When the call is transferred, the VRU may passthe above-described information to the live agent, e.g., by populatingthe information on the live agent's computer screen. At this point, themerchant bank may have sufficient information to determine whether toapprove the customer for the offered product or service.

It will be appreciated by those skilled in the art that passing thecredit, offer, and customer-provided information to the live agent, thelive agent is able to make final approval determination (e.g., asdescribed in block 255) and/or provide additional offers (e.g., relatedoffers or cross-selling) based on the more thorough and accurateinformation than if the live agent did not have this information. Inprior art systems and methods, the live agent did not receive all ofthis information from the VRU.

In block 255, the live agent (or processor) passes an approval response(or other offer result such as a denial or a request/requirement forfurther data or processing) to the customer. For instance, the liveagent (or processor) may determine whether to approve the customer forthe offered product or service based on the offer information, customerinformation, and customer credit score. Alternately, another entity suchas the processor may determine a final approval status. (It should beappreciated that “approval status” is meant to include approval, denial,or another category such as hold, need additional information, orqualified approval.)

If the customer is approved, the agent (or processor) may notify thecustomer of the approval (e.g., by indicating approval over the phone).The bank (or other provider) may then provide the product or service tothe customer or enroll the customer in the offered program, or otherwisetake steps towards providing the offered product or service to thecustomer. For instance, the processor may cause the offered credit cardto be mailed to the customer. If the customer is not approved, thecustomer may indicate the disapproval. In either case, the agent mayoffer additional products and/or services to the customer.

In block 260, one or more additional offers may be provided to thecustomer. These may be offers that are stored in the additional offerdatabase. The offers may comprise one or more offers for which thecustomer is pre-approved. These offers may also be provided to thecustomer based on customer preferences and other information. Forinstance, if the customer may be offered products and services based onthe location of the customer, e.g., a location identified by ANI, callerID, GPS, or other means. For instance, if the customer is identified tobe calling from a state other than the customer's home state, the bankmay presume that the customer is traveling and accordingly offer thecustomer a frequent flyer rewards program as a tie-in to a currentcredit card enrollment.

In block 265, the additional offers of block 260 are processed. Forinstance, the customer may be enrolled in a credit card rewards program,or the customer may open a new checking account.

Another Illustrative Process

FIG. 3 depicts a flow-chart for processing an unsolicited offeraccording to an embodiment of the invention. Because an unsolicitedoffer may not involve an offer or solicitation identifier, the exemplaryprocess for an unsolicited offer is different from the exemplary processfor a solicited offer.

Blocks 300-310 and 350-410 of FIG. 3 may occur as described forcorresponding blocks 215-220 and 235-265 of FIG. 2, respectively.

In block 320 of FIG. 3, the customer's location may be identified, e.g.,by ANI, caller ID, GPS, or other means. For instance, in someembodiments, the caller is prompted for a name and address. Speechrecognition (or alternatively, touchtone input) may be used to identifya zip code input by the caller (e.g., by voice or text). The processormay then access the location database 66 and identify all the streetscorresponding to that zip code. The caller may then input a streetaddress, e.g., by voice. The processor may identify a street addressbased on voice recognition and compare this address to the subset ofstreet results from the database. In this way, the processor can confirmthe customer's street address. The address extracted from the caller'sinput could also be compared to the address identified by ANI/Caller IDinformation for security purposes.

In block 330, customer-provided data such as offer data is received,e.g., from the customer by a live agent, VRU, or other processingelement. This action may occur as described for block 220 above,however, an offer identifier and solicitation identifier may not beinvolved. Rather, other offer and customer information may be received,e.g., in response to prompts by the processor or agent.

In block 340, customer-provided data is verified. For instance, thecustomer's address may be verified as described above in block 225.Credit information may be received from the credit bureau (e.g., inblock 370), and the credit information may enable the processor toverify that the customer's name matches a provided social securitynumber. Other databases and modules may be queried to identifyinformation associated with the customer. For instance, phone bookdatabases, Internet databases, employment databases, and other recordscan be used to verify customer information.

If the customer is a pre-existing bank customer, then the informationmay be verified as described above in the description of block 225.

Thus, the exemplary method described herein for the solicited andunsolicited approaches differs because the unsolicited approach does notuse offer identifiers and solicitation identifiers. It should beappreciated that an unsolicited offer response may be received from abank customer or other familiar person for which information is alreadystored, as in the exemplary solicited offer approach. In this scenario,an unsolicited offer may be processed in a manner very similar to thatof the solicited approach described above.

It should be appreciated that the embodiments described in FIGS. 2 and 3involve actions that need not be performed in the order presentedherein, nor must all of the actions be performed. Also, some of theactions may be performed more than once. For instance, information maybe verified as it is received, and the credit bureau may be queriedimmediately upon receiving the customer's social security number.

The embodiments of the present inventions are not to be limited in scopeby the specific embodiments described herein. For example, although manyof the embodiments disclosed herein have been described with referenceto banks and telephone telemarketing, the principles herein are equallyapplicable to other merchants and other methods of processing offers,e.g., processing offers on the Internet. Indeed, various modificationsof the embodiments of the present inventions, in addition to thosedescribed herein, will be apparent to those of ordinary skill in the artfrom the foregoing description and accompanying drawings. Thus, suchmodifications are intended to fall within the scope of the followingappended claims. Further, although some of the embodiments of thepresent invention have been described herein in the context of aparticular implementation in a particular environment for a particularpurpose, those of ordinary skill in the art will recognize that itsusefulness is not limited thereto and that the embodiments of thepresent inventions can be beneficially implemented in any number ofenvironments for any number of purposes. Accordingly, the claims setforth below should be construed in view of the full breath and spirit ofthe embodiments of the present inventions as disclosed herein.

What is claimed is:
 1. A computer-implemented method for processingapplications for products or services based on solicited offers made toconsumers, comprising: communicating, using a computer, a plurality ofoffers to a plurality of consumer recipients, each offer beingidentified by a solicitation identifier and an offer identifier; storingoffer information of said offers in an offer database that furtherincludes consumer identification information associated with theconsumer recipients; receiving a response to a specific offer from aspecific consumer recipient at a VRU via a communication link with thespecific consumer recipient; receiving at least some offeridentification data and consumer identification data from the specificconsumer recipient at the VRU, wherein the consumer identification datais received from a communication device identified with a telephonenumber and wherein the consumer identification data comprises theaddress of the specific consumer recipient; identifying the telephonenumber using automatic number identification (ANI); identifying alocation of the specific consumer recipient based on the identifiedtelephone number; using data received at the VRU to query the offerdatabase to identify other offers targeted to the specific consumerrecipient and data associated with those other targeted offers,including consumer identity verification data; verifying the identity ofthe specific consumer recipient based on the consumer identificationdata and the consumer identity verification data comprising verifyingthe address based on the identified location; transferring thecommunication link from the VRU to a live agent; and providing the liveagent with: (a) information received from the specific consumer at theVRU, and (b) data from the query of the offer database including dataregarding other targeted offers prior to the live agent commencingcommunication with the consumer.
 2. The method of claim 1, furthercomprising: issuing a request to a credit bureau for an approval resultreturned to the VRU, wherein the providing action further comprisesproviding the live agent with the results of the credit bureau request.3. The method of claim 2, wherein the credit bureau request comprises arequest for a credit score associated with the specific consumerrecipient, and wherein the results of the credit bureau request comprisethe credit score.
 4. The method of claim 3, wherein the credit score isbased on the consumer identification data.
 5. The method of claim 1,wherein the consumer identification data is associated with the specificconsumer recipient and comprises at least one selected from the groupconsisting of a name, an email address, an income, an amount of assets,a monthly housing payment, an address history, and an employmenthistory.
 6. The method of claim 1, wherein the act of receiving consumeridentification data comprises identifying words spoken by the specificconsumer recipient using voice recognition.
 7. The method of claim 1,wherein the specific offer comprises at least one of the following: anoffer to establish an account; an offer to purchase a certificate ofdeposit; an offer to purchase a stored value card; an offer to obtainfinancing; an offer to obtain account protection; an offer to enroll ina travel program; and an offer to enroll in a rewards program.
 8. Themethod of claim 1, wherein the data used at the VRU to query thedatabase comprises the offer identification data.
 9. The method of claim8, wherein the offer identification data comprises an offer identifier,wherein the offer identifier is pre-associated with the specific offerand the specific consumer recipient.
 10. A computer-implemented methodfor processing applications for products or services based on solicitedoffers made to consumers, comprising: communicating, using a computer, aplurality of offers to a plurality of consumer recipients, each offerbeing identified by a solicitation identifier and an offer identifier;storing offer information of said offers in an offer database thatfurther includes consumer identification information associated with theconsumer recipients and wherein the consumer identification datacomprises words spoken by the specific consumer recipient indicating astreet address; identifying a zip code associated with the specificconsumer recipient; identifying one or more streets associated with theidentified zip code; identifying the street address based on theidentified zip code and the identified one or more streets; receiving aresponse to a specific offer from a specific consumer recipient at a VRUvia a communication link with the specific consumer recipient; receivingat least some offer identification data and consumer identification datafrom the specific consumer recipient at the VRU; using data received atthe VRU to query the offer database to identify other offers targeted tothe specific consumer recipient and data associated with those othertargeted offers, including consumer identity verification data;verifying the identity of the specific consumer recipient based on theconsumer identification data and the consumer identity verificationdata; transferring the communication link from the VRU to a live agent;and providing the live agent with: (a) information received from thespecific consumer at the VRU, and (b) data from the query of the offerdatabase including data regarding other targeted offers prior to thelive agent commencing communication with the consumer.
 11. The method ofclaim 10, wherein the act of identifying the street address comprises:identifying speech recognition information based on the words spoken bythe specific consumer recipient; comparing the speech recognitioninformation to the one or more streets associated with the zip code. 12.The method of claim 11, wherein the act of identifying the streetaddress comprises identifying a specific street that is most closelyrelated to the speech recognition information.
 13. The method of claim1, wherein the acts of (i) receiving a response, (ii) receiving consumeridentification information, (iii) using data received at the VRU, (iv)verifying the identity of the specific consumer recipient, (v)transferring the communication link, and (vi) providing the live agentinformation and data, all occur during a single phone call.
 14. Themethod of claim 13, further comprising: providing one or more additionaloffers to the specific consumer recipient during the single phone call.15. The method of claim 13, wherein the one or more additional offersare selected to be provided to the specific consumer recipient based onat least one selected from the list comprising the specific consumerrecipient data, the consumer identification data, the data regardingother targeted offers, and pre-qualification information of the specificconsumer recipient.
 16. A computer-implemented method for processingapplications for products or services based on solicited offers made toconsumers, comprising: communicating, using a computer, a plurality ofoffers to a plurality of consumer recipients, each offer beingidentified by a solicitation identifier and an offer identifier; storingoffer information of said offers in an offer database that furtherincludes consumer identification information associated with theconsumer recipients; receiving a response to a specific offer from aspecific consumer recipient at a VRU via a communication link with thespecific consumer recipient; receiving at least some offeridentification data and consumer identification data from the specificconsumer recipient at the VRU; using data received at the VRU to querythe offer database to identify other offers targeted to the specificconsumer recipient and data associated with those other targeted offers,including consumer identity verification data; storing prior speechrecognition data of the specific consumer recipient, wherein the priorspeech recognition data is obtained during a prior communication withthe specific consumer recipient; verifying the identity of the specificconsumer recipient based on the consumer identification data and theconsumer identity verification data comprising processing the priorspeech recognition data; transferring the communication link from theVRU to a live agent; and providing the live agent with: (a) informationreceived from the specific consumer at the VRU, and (b) data from thequery of the offer database including data regarding other targetedoffers prior to the live agent commencing communication with theconsumer.
 17. The method of claim 16, wherein the act of processing theprior speech recognition data comprises comparing the speech recognitiondata to current speech recognition data.
 18. The method of claim 1,further comprising: checking a pre-approved database, wherein theproviding action further comprises providing the live agent withinformation based on the checking action.
 19. The method of claim 1,further comprising: prompting the customer for consumer identificationdata, wherein the act of receiving consumer identification data is basedon the act of prompting.
 20. A method for processing a customer offer,comprising: distributing an offer to a customer; receiving a response tothe offer from the customer through a customer communication device,wherein the response comprises customer address information, wherein thecustomer response is received from a telephone associated with atelephone number; identifying the telephone number using automaticnumber identification (ANI); automatically identifying a location of thecustomer communication device based on the identified telephone numberand one or more additional offers that may be targeted to the customer;wherein the act of identifying the location comprises identifying a zipcode; identifying an address of the customer, comprising: identifyingone or more streets associated with the zip code; receiving streetaddress information from the customer; and comparing the street addressinformation with the one or more streets associated with the zip code;verifying the customer address information based on the location of thecustomer communication device; prompting the customer for personalinformation, wherein the personal information comprises at least one ofa name of the customer, an email address of the customer, a physicaladdress of the customer, an income of the customer, an address historyof the customer, and an employment history of the customer; receivingthe personal information from the customer; and providing to a liveagent information about the distributed offer and the one or moreadditional offers that may be targeted to the customer prior to the liveagent commencing communication with the customer.
 21. The method ofclaim 20, wherein the offer comprises at least one selected from thegroup consisting of: an offer to establish an account; an offer topurchase a certificate of deposit; an offer to purchase a stored valuecard; an offer to obtain financing; an offer to obtain accountprotection; an offer to enroll in a travel program; and an offer toenroll in a rewards program.
 22. The method of claim 20, furthercomprising: verifying the personal information.
 23. The method of claim22, wherein the act of verifying the personal information comprisesidentifying the personal information by using voice recognition todistill words from customer speech.
 24. The method of claim 20, furthercomprising: passing the personal information to a credit bureau;receiving a credit score from the credit bureau, wherein the creditscore is based on the personal information.
 25. The method of claim 24,wherein the personal information comprises at least one of a name of thecustomer, an email address of the customer, a physical address of thecustomer, an income of the customer, an address history of the customer,and an employment history of the customer.
 26. The method of claim 20,further comprising: passing customer data to a credit bureau; andreceiving a credit score from the credit bureau, wherein the creditscore is based on the customer data.
 27. The method of claim 20, whereinthe street address information comprises speech recognition information,and wherein the act of comparing the street address information with theone or more streets comprises identifying a specific street that is mostclosely related to the speech recognition information.
 28. The method ofclaim 20, wherein the acts of receiving, identifying and providing occurduring a single phone call.
 29. The method of claim 28, wherein the oneor more additional offers are selected based on at least one of thecustomer data, personal information received from the customer, and acredit score associated with the customer.
 30. A method for processing acustomer offer, comprising: distributing an offer to a customer;receiving a response to the offer from the customer through a customercommunication device, wherein the response comprises customer addressinformation; automatically identifying the location of the customercommunication device and one or more additional offers that may betargeted to the customer; verifying the customer address informationbased on the location of the customer communication device; storingspeech recognition data of the customer; verifying the identity of thecustomer based on the speech recognition data; and providing to a liveagent information about the distributed offer and the one or moreadditional offers that may be targeted to the customer prior to the liveagent commencing communication with the customer.